Direct Adaptive Control

The paper discussed an adaptive friction compensation scheme based on Coulomb friction and a parameter identifier. The model reference adaptive system based on Coulomb friction was designed to compensate the friction on-line. The designed model reference adaptive parameter identifier was combined with the adaptive friction compensation system and the mover mass was identified by the parameter identifier to update mover mass in the model reference adaptive control system based on Coulomb friction. Simulation results show that the position tracking precision of system and robustness were improved.

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“…Based on Landau discrete time recursive parameter identification theory [10], the model reference adaptive method is…”

Section: The Identification Of Mover Mass Paremetermentioning

confidence: 99%

Adaptive friction compensation for permanent magnet linear synchronous motor

Wang

Lin

2009

2009 Chinese Control and Decision Conference

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“…Using Landau's discrete time-recursive parameter identification [18], the MRAI algorithm is designed as:…”

Section: B the Inertia Identification Based On Mraimentioning

confidence: 99%

Real-time IP controller based on neural network for permanent magnet synchronous motors

Cao

Fan

Zhu³

2009

2009 4th IEEE Conference on Industrial Electronics and Applications

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In servo motor drive applications, the variation of load inertia will degrade drive performance severely. Good dynamic and static performance of servo system requires controlling inertia robustly. In order to get the moment of rotational inertia, online identification methods based on model reference adaptive identification (MRAI) were developed in this paper. Then, a real-time IP position controller based on identified inertia is designed by neural network for permanent magnet synchronous motor (PMSM) servo system. The neural networks configuration is simple and reasonable, and the weight has definitely physical meaning. It has rapidly adjusting character to realize the real-time control. To demonstrate the advantages of the proposed real-time IP control scheme based on neural network, the simulation was executed in this research. The simulation results show that the proposed control scheme not only enhances the fast tracking performance, but also increases the robustness of the synchronous motor drive system. (24) Where, J Δ is the estimated incremental value of moment of inertia, namely, J J J − = Δˆ, J can be obtained from (12), Index Terms-PMSM, MRAI, real-time IP position controller, neural network

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“…Adaptive control is a control methodology capable of automatic and real‐time adjustments in control parameters with a view to maintaining a desired control performance for uncertain systems subject to unknown parameters 25‐27 . Early work 28‐31 on model reference adaptive control of distributed parameter systems (DPSs) focused on identifiability proof of infinite dimensional parameter vectors but required control action active over the entire PDE domain.…”

Section: Introductionmentioning

confidence: 99%

Spatiotemporal adaptive state feedback control of a linear parabolic partial differential equation

Wang

2023

Intl J Robust & Nonlinear

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This article deals with the issue of asymptotic stabilization for a linear parabolic partial differential equation (PDE) with an unknown space-varying reaction coefficient and multiple local piecewise uniform control. Clearly, the unknown reaction coefficient belongs to a function space. Hence, the fundamental difficulty for such issue lies in the lack of a conceptually simple but effective parameter identification technique in a function space. By the Lyapunov technique combined with a variant of Poincaré-Wirtinger inequality, an update law is derived for estimate of the unknown reaction coefficient in a function space.Then a spatiotemporal adaptive state feedback control law is constructed such that the estimate of the unknown coefficient is bounded and the closed-loop PDE is asymptotically stable in the sense of spatial  1 norm if a sufficient condition given in terms of space-time varying linear matrix inequalities (LMIs) is fulfilled for the estimated coefficient and the control gains. Both analytical and numerical approaches are proposed to construct a feasible solution to the space-time varying LMI problem. With the aid of the semigroup theory, the well-posedness and regularity of the closed-loop PDE is also analyzed. Moreover, two extensions of the proposed adaptive control scheme are discussed: the PDE in N-D space and the PDE with unknown diffusion and reaction coefficients. Finally, numerical simulation results are presented to support the proposed spatiotemporal adaptive control design.

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Direct Adaptive Control

Cited by 11 publications

References 0 publications

Adaptive friction compensation for permanent magnet linear synchronous motor

Adaptive friction compensation for permanent magnet linear synchronous motor

Real-time IP controller based on neural network for permanent magnet synchronous motors

Spatiotemporal adaptive state feedback control of a linear parabolic partial differential equation

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